The present invention is directed to a system which translates natural (human) language into an abstract formal language. This formal language is explicitly designed to serve as a universal template for further translations into a comprehensive variety of machine languages which are executable in specific operational environments. Extensive efforts have been made, many articles have been published, and many patents have been issued, all directed toward the goal of providing computers with the capacity to understand natural (human) language sufficiently well to respond reliably and accurately to directives issued from human users. Many companies and research groups, such as AT&T, IBM, and Microsoft, and an assortment of academic institutions, are presently working on natural language processing (NLP).
To date, many different approaches have been tried to provide a system which effectively converts natural language to a formal language for computer applications. One such approach is disclosed in an article published by Microsoft Corporation titled “Microsoft Research: Natural Language Processing Hits High Gear” dated May 3, 2000. The article discloses that Microsoft is heavily focused on a database of logical forms, called MindNet (™), and the creation of a machine translation application. It is stated that MindNet is an initiative in an area of research called “example-based processing”, whereby a computer processes input based on something it has encountered before. The MindNet database is created by storing and weighting the semantic graphs produced during the analysis of a document or collection of documents. The system uses this database to find links in meaning between words within a single language or across languages. These stored relationships among words give the system a basis for “understanding”, thereby allowing the system to respond to natural language input. MindNet apparently contains the contents of several dictionaries and an encyclopedia to increase its level of understanding. Another approach is disclosed in Microsoft U.S. Pat. No. 5,966,686. This approach provides a rule-based computer system for semantically analyzing natural language sentences. The system first transforms an input sentence into a syntactic parse tree. Semantic analysis then applies three sets of semantic rules to create an initial logical form graph from this tree. Additional rules provide semantically meaningful labels to create additional logical form graph models and to unify redundant elements. The final logical form graph represents the semantic analysis of the input sentence.
Yet another, and apparently more common, approach is provided by U.S. Pat. No. 5,895,466, wherein a database stores a plurality of answers which are indexed to natural language keys. The natural language device receives a natural language question over the network from a remote device and the question is analyzed using a natural language understanding system. Based on this analysis, the database is then queried and an answer is provided to the remote device.
Applicant is aware that various other approaches toward providing a conversion from natural language to some machine language have been tried. However, the prior art has not provided a truly effective conversion system of this sort.